rename pkg --> talweg

[talweg.git] / pkg / R / Forecaster.R

diff --git a/pkg/R/Forecaster.R b/pkg/R/Forecaster.R
deleted file mode 100644 (file)
index da8579b..0000000
--- a/pkg/R/Forecaster.R
+++ /dev/null
@@ -1,48 +0,0 @@
-#' Forecaster
-#'
-#' Forecaster (abstract class, implemented by all forecasters)
-#'
-#' @docType class
-#' @importFrom R6 R6Class
-#'
-#' @field .params List of computed parameters, for post-run analysis (dev)
-#' @field .pjump Function: how to predict the jump at day interface ?
-#'
-#' @section Methods:
-#' \describe{
-#' \item{\code{initialize(data, pjump)}}{
-#'   Initialize a Forecaster object with a Data object and a jump prediction function.}
-#' \item{\code{predictSerie(today,memory,horizon,...)}}{
-#'   Predict a new serie of \code{horizon} values at day index \code{today}
-#'   using \code{memory} days in the past.}
-#' \item{\code{predictShape(today,memory,horizon,...)}}{
-#'   Predict a new shape of \code{horizon} values at day index \code{today}
-#'   using \code{memory} days in the past.}
-#' \item{\code{getParameters()}}{
-#'   Return (internal) parameters.}}
-Forecaster = R6::R6Class("Forecaster",
-       private = list(
-               .params = list(),
-               .pjump = NULL
-       ),
-       public = list(
-               initialize = function(pjump)
-               {
-                       private$.pjump <- pjump
-                       invisible(self)
-               },
-               predictSerie = function(data, today, memory, horizon, ...)
-               {
-                       # Parameters (potentially) computed during shape prediction stage
-                       predicted_shape = self$predictShape(data, today, memory, horizon, ...)
-                       predicted_delta = private$.pjump(data,today,memory,horizon,private$.params,...)
-                       # Predicted shape is aligned it on the end of current day + jump
-                       predicted_shape+tail(data$getSerie(today),1)-predicted_shape[1]+predicted_delta
-               },
-               predictShape = function(data, today, memory, horizon, ...)
-                       NULL #empty default implementation: to implement in inherited classes
-               ,
-               getParameters = function()
-                       private$.params
-       )
-)